Various inspection devices (referred to as modality devices, hereinafter) used in image diagnosis are essential in the modern medicine, because those inspection devices can perform minimally invasive inspection of a human body. Advances in performance of the modality devices have allowed a quality image of high resolution to be obtained and accurate and precise inspection to be achieved in image diagnosis. For example, a computed tomography (CT) apparatus can obtain high-resolution three-dimensional information on a tissue inside an object, and a magnetic resonance imaging (MRI) apparatus can perform imaging in various ways depending on the modality device, such as an MR angiography (MRA) that images fresh blood containing no contrast medium by MRI. With advances in medical image digitalization, a hospital information system (HIS) that is an ordering system that processes a request from a doctor via an electronic network, a radiology information system (RIS) and a picture archiving and communication system (PACS) that accumulates images obtained by the modality device as electronic data have been developed.
Advances of the modality devices have enabled easy and detailed observation of the inside of a living body. An enormous amount of data can be obtained, and many modality devices obtain data in the form of volume data composed of a plurality of images. The amount of volume data is no less than thousands of images when a whole body is imaged, and it is burdensome to a doctor or the like who performs image interpretation of these data to make a diagnosis. Image interpretation is an important task for diagnosis of a disease or determination of a treatment plan. It is not easy to analyze the enormous amount of medical images to make an early decision, although there is a demand for early detection. In view of such circumstances, as inventions for supporting image diagnosis, there have been proposed a medical image processing apparatus that identifies an abnormal anatomical site and determines the degree of malignancy of the site by using a segmentation technique or the like (see Patent Literature 1, for example) and an image analyzing apparatus (see Patent Literature 2, for example) that determines a positional correspondence between images obtained in two different inspections.
Image interpretation and diagnosis need to be accurate, and to make an accurate diagnosis, an abnormal site or a site to be treated in the obtained medical image needs to be precisely grasped. However, to read an anatomical site from a medical image requires technical expertise. In view of this, techniques of representing or constructing an anatomical position in a human body through a mathematical approach have been studied and provided.
The “anatomical position” refers to a characteristic local structure in a human body (referred to as a local structure, hereinafter) that is important for understanding a medical image and serves as a mark when the human body is anatomically mapped. For example, an anterior arch (node) of a first cervical vertebra (cervical vertebra I) of a head is a local structure, a bifurcation of trachea in a chest is also a local structure, and an upper pole of a right kidney or the like in an abdomen is also a local structure. The position of the local structure (anatomical position) is automatically detected from the medical image obtained by the modality device, such as the X-ray CT device or the MRI device, by common image analysis, pattern recognition technique or the like.
A diagnostic reader (e.g. radiologist or the like) creates an image interpretation report based on the result of an image interpretation. In the image interpretation report, the anatomical site of an abnormality found in the image interpretation and the status of the abnormality are recorded as findings. Creation of the image interpretation report requires a task of selecting a representative image (referred to as a key image, hereinafter) that includes a finding and attaching a mark (referred to as an annotation, hereinafter) to the key image at a particular position of interest.
In a medical examination, the reader has to perform such an image interpretation report creation task for hundreds of patients. In some cases, an enormous amount of data containing hundreds or thousands of medical images is obtained per person in one X-ray CT or MRI imaging, and creation of an image interpretation report requires selecting a possible key image from among the enormous amount of medical image data and entering a finding for the selected key image. Such creation of an image interpretation report is a significant burden in image diagnosis.
In view of such circumstances, there is a demand for an image interpretation report creating apparatus that assists creation of an image interpretation report by making a list of a candidate site of a finding from a selected key image based on the position (anatomical position) of the local structure.